Realistic P&C Insurance Data: Policies, Claims, and Risk

Beyond Simple Policies

In the insurance world, a "Policy" is just the start. The real complexity lies in the events that happen after: accidents, claims, adjustments, and renewals. Static data generators can't capture this temporality.

📉 Claim Filed before Policy Start? Impossible with Aphelion.

Aphelion's Chronological Engine ensures strict cause-and-effect relationships. A claim cannot exist without an active policy, and a payout cannot happen without an approval decision.

Full P&C Capabilities

🏠 Multi-Line Policies

Product 1, Product 2, Product 3, and Product 4 with correct coverage limits.

💥 Complex Claims

Simulate Theft, Fire, Collision, and Liability claims with realistic descriptions.

🕵️ Fraud Signals

Inject subtle fraud patterns for training SIU (Special Investigation Unit) models.

💰 Premium History

Track monthly or annual payments, including late fees and lapse logic.

The "Lifecycle" Difference

Most generators create isolated tables. We create Linked Lifecycles. Here is what a typical generated entity looks like:

Day 0: User buys Product 1 (Cover: $500k, Ded: $1k).
Day 1-180: Monthly premiums paid on time.
Day 182: A "Water Damage" claim is filed.
Day 185: Claim status moves to "Under Review".
Day 192: Claim Approved -> Payout issued ($12,500).

// Example Generated Claim Object
{
  "type": "Water Damage",
  "status": "paid",
  "filed_date": "2024-06-15",
  "processed_date": "2024-06-25",
  "amount_filed": 15000.00,
  "amount_approved": 12500.00,
  "is_fraud": false
}

Why Actuaries Love This

Loss Ratio Testing

Validate your pricing models against simulated "Bad Years" (e.g., high storm activity) without waiting for reality to strike.

Lapse Prediction

Train churn models on synthetic customers who miss payments and eventually cancel.

Ready to test your Insurance Tech?

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